Strong fit for early-career data engineers who build reusable tools and work in financial data ecosystems, with a focus on collaborative, infrastructure-driven projects in Singapore.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Engineers Gate via Greenhouse
About EG:
Engineers Gate (EG) is a leading investment manager founded in 2014 as a quantitative, computer-driven trading firm. Today, EG operates as a diversified, multi-strategy investment platform that combines systematic research with selective discretionary approaches. EG's multi-manager platform allows independent investment teams to pursue distinct strategies while benefiting from shared infrastructure, risk management, and operational support. The firm’s collaborative groups of researchers, engineers, and investment professionals deploy sophisticated statistical models, proprietary technology, and a centralized data platform to isolate and solve challenging problem sets in the global financial markets.
About the Role:
The Data Engineer will join Engineers Gate’s Core Technology Team to build and scale the data platform that investment teams across the firm depend on. Working directly with portfolio managers and researchers, you will turn their data requirements into datasets, tools, and platform capabilities they can use. You will work across the full data lifecycle: evaluating new sources, understanding their quirks, building reliable processing workflows, and making data accessible through the platform. Alongside delivering new datasets, you will improve the infrastructure behind them, finding ways to make each new integration faster, more reliable, and easier to support.
As part of a small, focused team, you will take ownership of projects early and see your work reach users. You will learn from experienced engineers, build a broad understanding of data engineering and have room to contribute ideas and put them into practice. There is plenty to build, and your work will make a difference from the outset.
Key Responsibilities:
Take data projects from initial requirements through to delivery, working closely with
portfolio managers and quantitative researchers.
Investigate structured and unstructured financial datasets, understand their
coverage and limitations, and build robust workflows to process them.
Develop and improve the infrastructure that makes data available across the firm.
Build reusable tools for data analysis and quality checks, applying what you learn
from each dataset to the next.
Required Skills, Qualifications, and Experience:
Undergraduate degree in a STEM field.
Zero to two years of professional experience in software or data engineering.
Programming experience in Python.
Familiarity with data pipelines/ETL tools, relational databases, and/or SQL.